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Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Paper • 2212.14024 • Published • 3 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 37 -
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Paper • 2312.13382 • Published • 3 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 44
Shen Nan
wongshennan
AI & ML interests
None yet
Organizations
Compute
Foundation
Retrieval Augmented Generation
Evaluation
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A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25 -
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 23
ilya 30u30
Agents
-
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Paper • 2212.14024 • Published • 3 -
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Paper • 2310.03714 • Published • 37 -
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Paper • 2312.13382 • Published • 3 -
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent
Paper • 2312.10003 • Published • 44
Retrieval Augmented Generation
Compute
Evaluation
-
A Survey on Evaluation of Large Language Models
Paper • 2307.03109 • Published • 42 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25 -
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 23
Foundation
ilya 30u30